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135 articles for “Struggle”
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Artificial Intelligence Enhanced Waste Sorting and Classification System for Urban Recycling
Abstract: This study explores the potential of Artificial Intelligence (AI) and Machine Learning (ML) to enhance waste management efficiency within urban environments. Rapid urbanization has resulted in a surge of municipal waste, which current systems often struggle to manage effectively. The proposed AI-enhanced waste sorting and classification system aims to optimize waste collection routes and accurately forecast waste generation trends, thereby reducing operational costs, fuel consumption, and traffic congestion. Additionally, AI-driven …
Published in Current Trends in Signal Processing · Vol. 15, Issue 1, 2025 · pp. 23–32 Read article
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Great Women of India Like Ahilyabai Holkar, Rani Durgavati, Rani Bhabani, Rani Bhavashankari, Rani Rasmoni: Lessons for Making New India 2047
Abstract: Introduction: Since ancient times, women have struggled to navigate a society dominated by men. Despite years of planned development in India, women still have a lower status in society, and their socio-economic conditions remain significantly worse than those of men. Time has come to take Lessons from our Great Women, like Ahilyabai Holkar, Rani Durgavati, Rani Bhabani, Rani Bhavashankari, Rani Rasmoni and others to make New India 2047. Objective: The …
Published in OmniScience: A Multi-disciplinary Journal · Vol. 15, Issue 2, 2025 · pp. 39–44 Read article
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A Hybrid Algorithm for Processor Scheduling Using Game Theory Variants
Abstract: This study proposes a novel hybrid algorithm for processor scheduling in modern operating systems, integrating the strengths of traditional scheduling methods with game theory variants. Traditional schedulers often struggle to adapt to dynamic workload changes, leading to suboptimal performance. Our hybrid approach addresses this by treating processes as "players" in a game, where the "payoff" is CPU time. A base scheduler (e.g., Weighted Fair Queuing, Earliest Deadline First) provides a …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 1, 2025 · pp. 48–56 Read article
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Human-Robot Interactions and Social Robotics in Legal, Ethical, and Social Dimensions
Abstract: Human-robot interaction and social robotics have emerged as transformative fields, reshaping human engagement with intelligent machines. This evolution brings profound legal, ethical, and social challenges that demand critical exploration. Also, legal firms often struggle to keep pace with the advancements, raising questions about liability, accountability, and privacy in human-robot interaction. However, social robots, designed to operate in dynamic human environments, present ethical dilemmas around autonomy, trust, and preserving human dignity. …
Published in Journal of Advancements in Robotics · Vol. 12, Issue 1, 2025 · pp. 09–11 Read article
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FoodieHUB: Food Recipe Suggestion Using AI-ML On Web
Abstract: Finding a delicious recipe to cook with limited ingredients at home can be a challenging task. Many individuals struggle to prepare meals using only the ingredients they have on hand, creating uncertainty and limiting options. This project aims to develop a recipe recommendation system that utilizes machine learning algorithms to suggest recipes based on available ingredients, dietary preferences, cuisine types, cooking time, and user ratings. The project utilizes a Gradient …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 01–07 Read article
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Bridging the Gap and Unlocking Health Literacy: A Guide to Medical Report Clarity
Abstract: This research highlights the significant challenges faced by the general population in interpreting laboratory reports, medical charts, and other health-related documents. Studies show that approximately 9 out of 10 individuals struggle to understand such medical information, primarily due to low health literacy levels. This lack of understanding has become a hidden epidemic, affecting the way people engage with and respond to their own healthcare. While medical tests are essential for …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 31–36 Read article
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AI-Optimized Itinerary Design: Transforming the Future of Travel Planning
Abstract: The travel industry is struggling to meet the rising demand for efficient and personalized trip planning. Traditional methods often lack real-time updates and fail to adapt to individual preferences, necessitating innovative solutions. This study presents an AI-powered travel planner utilizing the Gemini API to enhance itinerary creation. By analyzing user preferences, interests, and real-time data, the system delivers tailored travel recommendations. Leveraging advanced technologies such as cloud computing, machine learning, …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 74–82 Read article
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Extraction of Impacted Lower 3rd Molars immediately after the Single Visit Endodontic treatment of 2nd Molar - A Case Series
Abstract: Patients who visit a dental clinic often anticipate fewer appointments and quicker recovery times. This expectation is particularly relevant when discussing impacted lower third molars in conjunction with decayed second molars. Dentists often struggle with the decision of whether to start endodontic treatment on the second molar or to proceed with extracting the third molar. This dilemma arises due to the absence of sufficient research or documentation specifically addressing the …
Published in Research and Reviews: A Journal of Dentistry · Vol. 16, Issue 2, 2025 · pp. 6–11 Read article
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Identification of Parameters Contributing To The Land Tenancy Security For The Tribal Areas of Jharkhand
Abstract: The issue of land tenancy security among tribal communities in Jharkhand, India, has long been a subject of concern due to historical, socio-economic, and legal complexities. This study aims to delve into the multifaceted aspects of tribal land tenancy security by identifying key parameters that influence it. Through a comprehensive analysis of historical records, legal frameworks, socio-economic conditions, and stakeholder perspectives, this research seeks to provide visions into the challenges …
Published in International Journal of Rural and Regional Development · Vol. 3, Issue 2, 2025 · pp. 1–13 Read article
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A Neuromorphic-Inspired, Low-Power VLSI Architecture for Edge AI in IoT Sensor Nodes
Abstract: As the proliferation of Internet of Things (IoT) devices continues to rise, there is an increasing demand for real-time, energy-efficient artificial intelligence (AI) processing directly at the network edge. Traditional edge AI accelerators, often based on deep learning models like convolutional neural networks (CNNs), struggle to meet the ultra-low-power requirements of battery-constrained IoT sensor nodes. In response to this challenge, this study introduces a neuromorphic-inspired, low-power very- large-scale integration (VLSI) …
Published in Journal of Microelectronics and Solid State Devices · Vol. 12, Issue 2, 2025 · pp. 41–47 Read article
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KSK Approach: An AI-Driven IoT Based Decision Making System’s Study
Abstract: Internet of Things (IoT) has promised a world of interrelated devices, generating vast amounts of data. Traditionally, IoT systems trusted on preprogrammed procedures and human intervention to process data and make decisions. This approach often struggled to hold the sheer size and density of IoT data, leading to inefficiencies and missed opportunities. However, the true budding of that data lies not simply in its collection, but in its interpretation and …
Published in Current Trends in Signal Processing · Vol. 15, Issue 2, 2025 · pp. 14–25 Read article
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Role of Reinforcement Learning in Improvement of Semiconductor Doping
Abstract: The semiconductor industry faces increasing challenges in achieving optimal doping profiles as device dimensions shrink and performance requirements intensify. Traditional doping optimization methods, while effective, often struggle with the complex, multi-dimensional parameter spaces characteristic of modern semiconductor manufacturing. This study explores the transformative role of reinforcement learning (RL) in improving semiconductor doping processes, examining how RL algorithms can autonomously optimize doping parameters to enhance device performance, reduce manufacturing costs, and …
Published in Journal of Semiconductor Devices and Circuits · Vol. 12, Issue 2, 2025 · pp. 23–34 Read article
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The Effect of Attachment Styles on Emotional Regulation Impacting Relationship Satisfaction: An Exploratory Case Study Design
Abstract: This study explores the impact of early attachment experiences, emotional regulation, and relationship dynamics among six participants through a qualitative case study approach. Using thematic and narrative analyses, the research identifies key patterns in emotional suppression, fear of abandonment, trust issues, and self-awareness. Participants' narratives reveal how childhood experiences with caregivers influenced their emotional regulation strategies and attachment styles in adulthood. Findings indicate that those with secure emotional upbringings exhibited …
Published in International Journal of Behavioral Sciences · Vol. 2, Issue 2, 2025 · pp. 1–17 Read article
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Next-Gen Techniques for Bottleneck Detection in High-Performance Computing
Abstract: Modern computing systems face new challenges in bottleneck detection and mitigation due to their increasing complexity which stems from multi-core architectures alongside distributed platforms and real-time processing needs. Traditional methods like hardware profiling and static analysis which used to work well now struggle to keep up with the changing conditions of dynamic system behaviors and diverse computing environments along with variable workload patterns. The current limitations restrict their capability to …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 2, 2025 · pp. 09–14 Read article
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Efficient Clustering Techniques for Data Stream Mining
Abstract: Data mining mainly works on a massive database for storing heavy amount of data. It is generally essential for extracting the meaning insights from the massive, continuously growing database. The traditional method often struggles with sheer volume and the dynamic nature of the modern data. Data stream mining allows for the real-time analysis, means insights are generated as the data arrives, and not after the long batch process. This continuous …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 2, 2025 · pp. 26–32 Read article
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Smart AI-Enhanced Tool for Comprehensive Mock Interview Practice
Abstract: Job seekers often struggle with interview preparation due to a lack of structured practice, real-time feedback, and a realistic interview environment. Traditional methods, such as self-practice or mock interviews with peers, may not provide an accurate assessment of a candidate’s readiness for real-world job interviews. This research work introduces an AI-based mock interview tool designed to enhance skills based on a user's job profile. The platform is built using React …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 12, Issue 2, 2025 · pp. 20–25 Read article
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Support Vector Machine Inspired Load Forecasting of a State University in Haryana
Abstract: Estimating the possible environmental impact and determining probable capital requirements are made easier with a solid grasp of electricity demand. Beginning in the middle of the 20th century, demand forecasting for electric power networks was studied theoretically. Prior to that, the study of demand forecasting had not developed because of the small scale of power networks. With the use of statistical prediction techniques, plans for the electric power industry have …
Published in Trends in Electrical Engineering · Vol. 15, Issue 2, 2025 · pp. 33–40 Read article
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Role of Artificial Intelligence in Transforming Personalized Learning in Education
Abstract: Artificial Intelligence (AI) is revolutionizing personalized education by tailoring learning experiences to meet each student's unique needs. Through advanced algorithms, AI can adapt educational content to align with individual learning speeds, preferences, and styles. Technologies such as adaptive learning systems, smart tutoring tools, and AI-powered assessments offer instant feedback and assist teachers in quickly identifying areas where students may be struggling. Additionally, predictive analytics help anticipate student outcomes, enabling early …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 12, Issue 3, 2025 · pp. 27–32 Read article
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Artificial Intelligence and Personalized Learning
Abstract: Artificial Intelligence is transforming education by delivering customized learning pathways that align with each learner’s unique abilities and areas for improvement. Traditional teaching often struggles to meet individual needs; however, AI-powered systems analyse learning patterns in real time, ensuring customized lessons. Virtual tutors and AI chatbots provide instant feedback and 24/7 support, improving comprehension. Gamified learning, combined with augmented and virtual reality, transforms education into a more engaging and enjoyable …
Published in Current Trends in Information Technology · Vol. 15, Issue 3, 2025 · pp. 11–18 Read article
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Challenges of E-learning for Learners
Abstract: E-learning, the use of digital technologies for education, has become increasingly popular in recent years. However, learners face several challenges in this mode of learning. This abstract explores some of the key challenges faced by learners in e-learning environments. E-learning environments often lack the interpersonal engagement found in traditional classrooms, such as collaborative discussions, peer support, and networking opportunities, which can result in feelings of isolation and reduced motivation. Success …
Published in International Journal of Machine Systems and Manufacturing Technology · Vol. 3, Issue 2, 2025 · pp. 7–15 Read article